IT operations leaders
Fewer, truer incidents to handle.
Capability
Network & IT AIOps
Fewer alarms, faster root cause, and outages caught before customers call.
Alarm-to-incident compressionMean time to detect and to restoreChange-related incident rateAutomated remediation coverage
The service at a glance
The problem, our work, your result
- Business problem
IT and network teams drown in alerts, and real incidents hide in the noise.
Monitoring tools each raise their own alarms, so engineers chase symptoms while the root cause spreads.
- What we do
We apply AI to your operational data: correlate alerts into incidents, find root causes, predict failures and automate the fixes that are safe to automate.
- What you receive
- Alert correlation and noise reduction
- Root cause analysis
- Failure prediction
- Safe automated remediation
Who it is for
Built for the people who own the decision
Network teams
Root cause in minutes, not hours.
CFO and finance
Less downtime and overtime.
Risk, compliance and security
Controlled, auditable automation.
The goal: an AI-ready organisation
Where this service moves you
Data readyThis service
Connected, clean, governed and allowed for AI use.
KPIs ready
Agreed measures, one definition each, a named owner.
Organisation readyThis service
Roles, decision rights and skills to adopt AI safely.
=AI that reaches production and creates value
Approach
How we work with you
- 01
Consolidate
Bring monitoring data together.
- 02
Correlate
Group alerts into real incidents.
- 03
Predict
Model failures before they happen.
- 04
Automate
Automate proven, safe fixes.
Engagement options
Start where you are
Alert noise review
Where AI cuts noise first.
AIOps pilot
Correlation and root cause live.
Autonomous operations
Prediction plus safe automation.
Scope
What is in, what is not
Included
- Operational data platform
- Correlation and prediction models
- Automation playbooks
- Monitoring tool integration
Handled separately
- Monitoring tool licences
- Network hardware
Bilytica frameworks behind this service
Our own methods, not a generic playbook
AGENT
All Bilytica frameworksAgent Operations Framework
Autonomy tiers, tool boundaries and human checkpoints, so agents can act without becoming a liability.
See the frameworkDELIVERAI Delivery Framework
A gated path from idea to live service, with evidence at every step.
See the frameworkIn short
What this actually is
Correlation and anomaly detection across network, infrastructure and application telemetry: alarm storms collapsed into incidents, probable root cause ranked with evidence, and automated remediation for the runbooks that are safe to automate. Built for NOCs drowning in events rather than short of dashboards.
Key points
What matters before you buy
- 01
Noise reduction is the first win
Collapsing correlated alarms into a single incident gives the NOC its attention back.
- 02
Root cause needs topology
Without an accurate dependency map, correlation degrades into guessing by timestamp.
- 03
Automate the boring runbooks first
Restart, reroute, scale and clear are safe candidates; anything customer-affecting keeps an approval gate.
- 04
Customer impact is the real metric
Ranking incidents by affected customers and revenue beats ranking by device severity.
Delivery
How we build it
Foundation check
Before any buildWe inspect the systems, the data behind them and the quality of the records this capability will depend on, then write down what has to be fixed before anything is built.
Narrow first release
First releaseOne workflow, one team, real traffic, measured against the baseline we captured before we started.
Controls and evaluation
Runs in parallelGuardrails, approval gates, evaluation sets, logging and the evidence pack your auditor and your regulator will ask for.
Scale and hand over
After sign-offAdditional workflows, sites or languages, then runbooks and training so your team can operate it without us.
Data foundation
What has to be true in your data first
Great AI cannot hide bad data. These are the conditions this capability depends on, we fix them as part of delivery, not after go-live.
- Event, metric, log and trace streams with synchronised clocks.
- A current CMDB or topology graph, including service dependencies.
- Incident history with real resolution codes for supervised learning.
- Change records, a large share of incidents follow a change.
Controls
Guardrails we put around it
A human owns every consequential decision
Agents draft, route and execute reversible steps. Anything that moves money, changes a record of consequence or affects a person's rights stops at a named human approver with the reasoning attached.
Every action is logged and replayable
Inputs, retrieved context, model version, output and the human decision are written to an immutable log, so an auditor can reconstruct any single interaction months later.
Accuracy is monitored, not assumed
A held-out evaluation set runs on every model or prompt change, with drift alerts and a documented rollback path when quality moves.
Data stays where your regulator requires
In-country, in-region or on-premise deployment, with the model portfolio right-sized to the workload instead of routing everything to a frontier endpoint abroad.
Fit
Systems it plugs into, and what it moves
Integrations
ServiceNowSplunkElasticGrafana / PrometheusNetcoolNokia / Ericsson / Huawei OSSKubernetes
KPIs it moves
- • Alarm-to-incident compression
- • Mean time to detect and to restore
- • Change-related incident rate
- • Automated remediation coverage
- • Customer-impacting outage minutes
By industry